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1. Influence of Potassium, Sulfur, and Zinc Fertilizer on Corn and Soybean Grown on High Tetsing SoilThe influence of potassium, sulfur and zinc fertilizer on corn and soybean yields grown on high testing soils was studied at two locations in Eastern South Dakota over a period of six years. Treatments were 50 Ibla K,O, 25 Ibla sulfur and 5 Ib/a zinc. The treatments were applied to the same plots at each location every year. Soil test levels were in the high range for all elements in question and additional nutrients would not have been recommended by the South Dakota State University Soil Testing... |
2. Sulfur Influence on Corn and Soybean Yields in Eastern South DakotaClean air legislation, the increasing use of conservation tillage, and the manufacture of phosphorus fertilizers without sulfur have all contributed to lowering soil sulfur (S) availability to crops. Soil S availability has been affected to some extent by all three issues in eastern South Dakota. Hilltop erosion has exposed subsoil in which the pH is higher and organic matter content is lower than at lower landscape positions. In some eroded shoulder positions of the landscape in no-till fields.... |
3. Influence of Soil Test Phosphorus on Phosphorus Runoff Losses from South Dakota SoilsApplications of manure and fertilizer phosphorus (P) to soil in excess of optimal crop requirements leads to a buildup of soil test phosphorus (STP) and increases the risk of offsite transfer of P during heavy precipitation events. The first step to developing effective manure and fertilizer P application strategies for South Dakota is to evaluate the relationship that exists between soil and runoff P. The objectives of this study were to: 1) determine the relationship between STP and runoff P concentrations... |
4. Integrating Management Zones and Canopy Sensing for Improved Nitrogen Recommendation AlgorithmsActive crop canopy sensors have been studied as a tool to direct spatially variable nitrogen (N) fertilizer applications in maize, with the goal of increasing the synchrony between N supply and crop demand and thus improving N use efficiency (NUE). However, N recommendation algorithms have often proven inaccurate in certain subfield regions due to local spatial variability. Modifying these algorithms by integrating soil-based management zones (MZ) may improve their accuracy... J. Crowther, J. Parrish, R. Ferguson, J. Luck, K. Glewen, T. Shaver, D. Krull, L. Thompson, N. Mueller, B. Krienke, T. Mieno, T. Ingram |
5. Comparison of Ground-Based Active Crop Canopy Sensor and Aerial Passive Crop Canopy Sensor for In-Season Nitrogen ManagementCrop canopy sensors represent one tool available to help calculate a reactive in-season nitrogen (N) application rate in corn. When utilizing such systems, corn growers must decide between using active versus passive crop canopy sensors. The objectives of this study was to 1) determine the correlation between N management by remote sensing using a passive sensor and N management using proximal sensing with an active sensors. Treatments were arranged as field length strips in a randomized complete... J. Parrish, R. Ferguson, J. Luck, K. Glewen, L. Thompson, B. Krienke, N. Mueller, T. Ingram, D. Krull, J. Crowther, T. Shaver, T. Mieno |